""" LifeCycleCosts module calculates the life cycle costs of one building SPDX - License - Identifier: LGPL - 3.0 - or -later Copyright © 2022 Project Author Pilar Monsalvete Alvarez de Uribarri pilar_monsalvete@concordia.ca Code contributor Oriol Gavalda Torrellas oriol.gavalda@concordia.ca """ import math import pandas as pd import numpy_financial as npf import hub.helpers.constants as cte from costs import SKIN_RETROFIT, SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, PERCENTAGE_CREDIT,INTEREST_RATE,CREDIT_YEARS class LifeCycleCosts: """ Life cycle cost class """ def __init__(self, building, archetype, number_of_years, consumer_price_index, electricity_peak_index, electricity_price_index, gas_price_index, discount_rate, retrofitting_scenario, fuel_type): self._building = building self._number_of_years = number_of_years self._consumer_price_index = consumer_price_index self._electricity_peak_index = electricity_peak_index self._electricity_price_index = electricity_price_index self._gas_price_index = gas_price_index self._discount_rate = discount_rate self._archetype = archetype self._end_of_life_cost = 0 self._capital_costs_at_year_0 = 0 self._items = 0 self._fuels = 0 self._concepts = 0 self._retrofitting_scenario = retrofitting_scenario self._total_floor_area = 0 self._fuel_type = fuel_type for internal_zone in building.internal_zones: for thermal_zone in internal_zone.thermal_zones: self._total_floor_area += thermal_zone.total_floor_area # todo: revise if it works rng = range(number_of_years) self._yearly_capital_costs = pd.DataFrame(index=rng, columns=['B2010_opaque_walls', 'B2020_transparent', 'B3010_opaque_roof', 'B10_superstructure', 'D301010_photovoltaic_system', 'D3020_heat_generating_systems', 'D3030_cooling_generation_systems', 'D3040_distribution_systems', 'D3080_other_hvac_ahu', 'D5020_lighting_and_branch_wiring'], dtype='float') self._yearly_end_of_life_costs = pd.DataFrame(index=rng, columns=['End_of_life_costs'], dtype='float') self._yearly_operational_costs = pd.DataFrame(index=rng, columns=['Fixed_costs_electricity_peak', 'Fixed_costs_electricity_monthly', 'Variable_costs_electricity', 'Fixed_costs_gas', 'Variable_costs_gas'], dtype='float') self._yearly_maintenance_costs = pd.DataFrame(index=rng, columns=['Heating_maintenance', 'Cooling_maintenance', 'PV_maintenance'], dtype='float') self._yearly_operational_incomes = pd.DataFrame(index=rng, columns=['Incomes electricity'], dtype='float') self._yearly_capital_incomes = pd.DataFrame(index=rng, columns=['Subsidies construction', 'Subsidies HVAC', 'Subsidies PV'], dtype='float') def calculate_capital_costs(self): """ Calculate capital cost :return: pd.DataFrame """ building = self._building archetype = self._archetype surface_opaque = 0 surface_transparent = 0 surface_roof = 0 surface_ground = 0 capital_cost_pv = 0 capital_cost_opaque = 0 capital_cost_ground = 0 capital_cost_transparent = 0 capital_cost_roof = 0 capital_cost_heating_equipment = 0 capital_cost_cooling_equipment = 0 capital_cost_distribution_equipment = 0 capital_cost_other_hvac_ahu = 0 capital_cost_lighting = 0 total_floor_area = self._total_floor_area for internal_zone in building.internal_zones: for thermal_zone in internal_zone.thermal_zones: for thermal_boundary in thermal_zone.thermal_boundaries: if thermal_boundary.type == 'Ground': surface_ground += thermal_boundary.opaque_area elif thermal_boundary.type == 'Roof': surface_roof += thermal_boundary.opaque_area elif thermal_boundary.type == 'Wall': surface_opaque += thermal_boundary.opaque_area * (1 - thermal_boundary.window_ratio) surface_transparent += thermal_boundary.opaque_area * thermal_boundary.window_ratio chapters = archetype.capital_cost peak_heating = building.heating_peak_load[cte.YEAR][0]/1000 peak_cooling = building.cooling_peak_load[cte.YEAR][0]/1000 # todo: change area pv when the variable exists roof_area = 0 for roof in building.roofs: roof_area += roof.solid_polygon.area surface_pv = roof_area * 0.5 self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = 0 self._yearly_capital_costs.loc[0]['B2020_transparent'] = 0 self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = 0 self._yearly_capital_costs.loc[0]['B10_superstructure'] = 0 self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'] = 0 self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'] = 0 self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'] = 0 self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'] = 0 self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] = 0 self._yearly_capital_incomes.loc[0, 'Subsidies construction'] = 0 self._yearly_capital_incomes.loc[0, 'Subsidies HVAC'] = 0 self._yearly_capital_incomes.loc[0, 'Subsidies PV'] = 0 self._yearly_capital_costs.fillna(0, inplace=True) if self._retrofitting_scenario in (SKIN_RETROFIT, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV): chapter = chapters.chapter('B_shell') capital_cost_opaque = surface_opaque * chapter.item('B2010_opaque_walls').refurbishment[0] capital_cost_transparent = surface_transparent * chapter.item('B2020_transparent').refurbishment[0] capital_cost_roof = surface_roof * chapter.item('B3010_opaque_roof').refurbishment[0] capital_cost_ground = surface_ground * chapter.item('B10_superstructure').refurbishment[0] self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = capital_cost_opaque * (1-PERCENTAGE_CREDIT) self._yearly_capital_costs.loc[0]['B2020_transparent'] = capital_cost_transparent * (1-PERCENTAGE_CREDIT) self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = capital_cost_roof * (1-PERCENTAGE_CREDIT) self._yearly_capital_costs.loc[0]['B10_superstructure'] = capital_cost_ground * (1-PERCENTAGE_CREDIT) if self._retrofitting_scenario in (SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV): chapter = chapters.chapter('D_services') capital_cost_pv = surface_pv * chapter.item('D301010_photovoltaic_system').initial_investment[0] self._yearly_capital_costs.loc[0]['D301010_photovoltaic_system'] = capital_cost_pv capital_cost_heating_equipment = ( peak_heating * chapter.item('D3020_heat_generating_systems').initial_investment[0] ) capital_cost_cooling_equipment = ( peak_cooling * chapter.item('D3030_cooling_generation_systems').initial_investment[0] ) capital_cost_distribution_equipment = ( peak_cooling * chapter.item('D3040_distribution_systems').initial_investment[0] ) capital_cost_other_hvac_ahu = peak_cooling * chapter.item('D3080_other_hvac_ahu').initial_investment[0] capital_cost_lighting = total_floor_area * chapter.item('D5020_lighting_and_branch_wiring').initial_investment[0] self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'] = capital_cost_heating_equipment * (1-PERCENTAGE_CREDIT) self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'] = capital_cost_cooling_equipment * (1-PERCENTAGE_CREDIT) self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'] = capital_cost_distribution_equipment * (1-PERCENTAGE_CREDIT) self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'] = capital_cost_other_hvac_ahu * (1-PERCENTAGE_CREDIT) self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] = capital_cost_lighting * (1-PERCENTAGE_CREDIT) for year in range(1, self._number_of_years): chapter = chapters.chapter('D_services') costs_increase = math.pow(1 + self._consumer_price_index, year) self._yearly_capital_costs.loc[year, 'B2010_opaque_walls'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS, capital_cost_opaque * (PERCENTAGE_CREDIT)) self._yearly_capital_costs.loc[year, 'B2020_transparent'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS, capital_cost_transparent * (PERCENTAGE_CREDIT) ) self._yearly_capital_costs.loc[year, 'B3010_opaque_roof'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,capital_cost_roof * (PERCENTAGE_CREDIT)) self._yearly_capital_costs.loc[year, 'B10_superstructure'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS, capital_cost_ground * (PERCENTAGE_CREDIT)) self._yearly_capital_costs.loc[year, 'D3020_heat_generating_systems'] = -npf.pmt(INTEREST_RATE,CREDIT_YEARS, capital_cost_heating_equipment * (PERCENTAGE_CREDIT)) self._yearly_capital_costs.loc[year, 'D3030_cooling_generation_systems'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS, capital_cost_cooling_equipment * (PERCENTAGE_CREDIT)) self._yearly_capital_costs.loc[year, 'D3040_distribution_systems'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS, capital_cost_distribution_equipment * (PERCENTAGE_CREDIT)) self._yearly_capital_costs.loc[year, 'D3080_other_hvac_ahu'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS, capital_cost_other_hvac_ahu * (PERCENTAGE_CREDIT)) self._yearly_capital_costs.loc[year, 'D5020_lighting_and_branch_wiring'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS, capital_cost_lighting * (PERCENTAGE_CREDIT)) if (year % chapter.item('D3020_heat_generating_systems').lifetime) == 0: reposition_cost_heating_equipment = peak_heating * chapter.item('D3020_heat_generating_systems').reposition[0] \ * costs_increase self._yearly_capital_costs.loc[year, 'D3020_heat_generating_systems'] += reposition_cost_heating_equipment if (year % chapter.item('D3030_cooling_generation_systems').lifetime) == 0: reposition_cost_cooling_equipment = peak_cooling \ * chapter.item('D3030_cooling_generation_systems').reposition[0] \ * costs_increase self._yearly_capital_costs.loc[year, 'D3030_cooling_generation_systems'] += reposition_cost_cooling_equipment if (year % chapter.item('D3080_other_hvac_ahu').lifetime) == 0: reposition_cost_hvac_ahu = peak_cooling * chapter.item('D3080_other_hvac_ahu').reposition[0] * costs_increase self._yearly_capital_costs.loc[year, 'D3080_other_hvac_ahu'] = reposition_cost_hvac_ahu if (year % chapter.item('D5020_lighting_and_branch_wiring').lifetime) == 0: reposition_cost_lighting = total_floor_area * chapter.item('D5020_lighting_and_branch_wiring').reposition[0] \ * costs_increase self._yearly_capital_costs.loc[year, 'D5020_lighting_and_branch_wiring'] += reposition_cost_lighting if self._retrofitting_scenario in (SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV): if (year % chapter.item('D301010_photovoltaic_system').lifetime) == 0: self._yearly_capital_costs.loc[year]['D301010_photovoltaic_system'] += surface_pv \ * chapter.item( 'D301010_photovoltaic_system').reposition[0] * costs_increase capital_cost_skin = capital_cost_opaque + capital_cost_ground + capital_cost_transparent + capital_cost_roof capital_cost_hvac = ( capital_cost_heating_equipment + capital_cost_cooling_equipment + capital_cost_distribution_equipment + capital_cost_other_hvac_ahu + capital_cost_lighting ) self._yearly_capital_incomes.loc[0, 'Subsidies construction'] = ( capital_cost_skin * archetype.income.construction_subsidy/100 ) self._yearly_capital_incomes.loc[0, 'Subsidies HVAC'] = capital_cost_hvac * archetype.income.hvac_subsidy/100 self._yearly_capital_incomes.loc[0, 'Subsidies PV'] = capital_cost_pv * archetype.income.photovoltaic_subsidy/100 self._yearly_capital_incomes.fillna(0, inplace=True) return self._yearly_capital_costs, self._yearly_capital_incomes def calculate_end_of_life_costs(self): """ Calculate end of life costs :return: pd.DataFrame """ archetype = self._archetype total_floor_area = self._total_floor_area for year in range(1, self._number_of_years + 1): price_increase = math.pow(1 + self._consumer_price_index, year) if year == self._number_of_years: self._yearly_end_of_life_costs.at[ year, 'End_of_life_costs'] = total_floor_area * archetype.end_of_life_cost * price_increase self._yearly_end_of_life_costs.fillna(0, inplace=True) return self._yearly_end_of_life_costs def calculate_total_floor_area(self): total_floor_area = self._total_floor_area return total_floor_area @property def calculate_total_operational_costs(self): """ Calculate total operational costs :return: pd.DataFrame """ building = self._building archetype = self._archetype total_floor_area = self._total_floor_area factor_residential = total_floor_area / 80 # todo: split the heating between fuels fixed_gas_cost_year_0 = 0 variable_gas_cost_year_0 = 0 electricity_heating = 0 domestic_hot_water_electricity = 0 if self._fuel_type == 1: fixed_gas_cost_year_0 = archetype.operational_cost.fuels[1].fixed_monthly * 12 * factor_residential variable_gas_cost_year_0 = ( (building.heating_consumption[cte.YEAR][0] + building.domestic_hot_water_consumption[cte.YEAR][0]) / 1000 * archetype.operational_cost.fuels[1].variable[0] ) if self._fuel_type == 0: electricity_heating = building.heating_consumption[cte.YEAR][0] / 1000 domestic_hot_water_electricity = building.domestic_hot_water_consumption[cte.YEAR][0] / 1000 electricity_cooling = building.cooling_consumption[cte.YEAR][0] / 1000 electricity_lighting = building.lighting_electrical_demand[cte.YEAR]['insel meb'] / 1000 electricity_plug_loads = building.appliances_electrical_demand[cte.YEAR]['insel meb'] / 1000 electricity_distribution = 0 total_electricity_consumption = ( electricity_heating + electricity_cooling + electricity_lighting + domestic_hot_water_electricity + electricity_plug_loads + electricity_distribution ) print(f'electricity consumption {total_electricity_consumption}') # todo: change when peak electricity demand is coded. Careful with factor residential peak_electricity_demand = 0.1*total_floor_area # self._peak_electricity_demand variable_electricity_cost_year_0 = total_electricity_consumption * archetype.operational_cost.fuels[0].variable[0] peak_electricity_cost_year_0 = peak_electricity_demand * archetype.operational_cost.fuels[0].fixed_power * 12 monthly_electricity_cost_year_0 = archetype.operational_cost.fuels[0].fixed_monthly * 12 * factor_residential for year in range(1, self._number_of_years + 1): price_increase_electricity = math.pow(1 + self._electricity_price_index, year) price_increase_peak_electricity = math.pow(1 + self._electricity_peak_index, year) price_increase_gas = math.pow(1 + self._gas_price_index, year) self._yearly_operational_costs.at[year, 'Fixed_costs_electricity_peak'] = ( peak_electricity_cost_year_0 * price_increase_peak_electricity ) self._yearly_operational_costs.at[year, 'Fixed_costs_electricity_monthly'] = ( monthly_electricity_cost_year_0 * price_increase_peak_electricity ) self._yearly_operational_costs.at[year, 'Variable_costs_electricity'] = float( variable_electricity_cost_year_0 * price_increase_electricity ) self._yearly_operational_costs.at[year, 'Fixed_costs_gas'] = fixed_gas_cost_year_0 * price_increase_gas self._yearly_operational_costs.at[year, 'Variable_costs_gas'] = ( variable_gas_cost_year_0 * price_increase_peak_electricity ) self._yearly_operational_costs.at[year, 'Variable_costs_gas'] = ( variable_gas_cost_year_0 * price_increase_peak_electricity ) self._yearly_operational_costs.fillna(0, inplace=True) return self._yearly_operational_costs def calculate_total_operational_incomes(self, retrofitting_scenario): """ Calculate total operational incomes :return: pd.DataFrame """ building = self._building if cte.YEAR not in building.onsite_electrical_production: onsite_electricity_production = 0 else: if retrofitting_scenario == 0 or retrofitting_scenario == 1: onsite_electricity_production = 0 else: onsite_electricity_production = building.onsite_electrical_production[cte.YEAR][0]/1000 for year in range(1, self._number_of_years + 1): price_increase_electricity = math.pow(1 + self._electricity_price_index, year) # todo: check the adequate assignation of price. Pilar price_export = 0.075 # archetype.income.electricity_export self._yearly_operational_incomes.loc[year, 'Incomes electricity'] = ( onsite_electricity_production * price_export * price_increase_electricity ) self._yearly_operational_incomes.fillna(0, inplace=True) return self._yearly_operational_incomes def calculate_total_maintenance_costs(self): """ Calculate total maintenance costs :return: pd.DataFrame """ building = self._building archetype = self._archetype # todo: change area pv when the variable exists roof_area = 0 for roof in building.roofs: roof_area += roof.solid_polygon.area surface_pv = roof_area * 0.5 peak_heating = building.heating_peak_load[cte.YEAR][0]/1000 peak_cooling = building.heating_peak_load[cte.YEAR][0]/1000 maintenance_heating_0 = peak_heating * archetype.operational_cost.maintenance_heating maintenance_cooling_0 = peak_cooling * archetype.operational_cost.maintenance_cooling maintenance_pv_0 = surface_pv * archetype.operational_cost.maintenance_pv for year in range(1, self._number_of_years + 1): costs_increase = math.pow(1 + self._consumer_price_index, year) self._yearly_maintenance_costs.loc[year, 'Heating_maintenance'] = ( maintenance_heating_0 * costs_increase ) self._yearly_maintenance_costs.loc[year, 'Cooling_maintenance'] = ( maintenance_cooling_0 * costs_increase ) self._yearly_maintenance_costs.loc[year, 'PV_maintenance'] = ( maintenance_pv_0 * costs_increase ) self._yearly_maintenance_costs.fillna(0, inplace=True) return self._yearly_maintenance_costs